Genome polishing and variant calling.
The GenomicConsensus
package provides the variantCaller
tool,
which allows you to apply the Quiver or Arrow algorithm to mapped
PacBio reads to get consensus and variant calls.
Latest version can be installed via bioconda package genomicconsensus
.
Please refer to our official pbbioconda page for information on Installation, Support, License, Copyright, and Disclaimer.
Quiver is the legacy consensus model based on a conditional random field approach. Quiver enables consensus accuracies on genome assemblies at accuracies approaching or even exceeding Q60 (one error per million bases). If you use the HGAP assembly protocol in SMRTportal 2.0 or later, Quiver runs automatically as the final "assembly polishing" step.
Over the years Quiver has proven difficult to train and develop, so we are phasing it out in favor of the new model, Arrow. Arrow is an improved consensus model based on a more straightforward hidden Markov model approach.
Quiver is supported for PacBio RS data. Arrow is supported for PacBio Sequel data and RS data with the P6-C4 chemistry.
Basic usage is as follows:
% quiver aligned_reads{.cmp.h5, .bam, .fofn, or .xml} \
> -r reference{.fasta or .xml} -o variants.gff \
> -o consensus.fasta -o consensus.fastq
quiver
is a shortcut for variantCaller --algorithm=quiver
.
Naturally, to use arrow you could use the arrow
shortcut or
variantCaller --algorithm=arrow
.
in this example we perform haploid consensus and variant calling on
the mapped reads in the aligned_reads.bam
which was aligned to
reference.fasta
. The reference.fasta
is only used for
designating variant calls, not for computing the consensus. The
consensus quality score for every position can be found in the output
FASTQ file.
Note that 2.3 SMRTanalysis does not support "dataset" input (FOFN or XML files); those who need this feature should wait for the forthcoming release of SMRTanalysis 3.0 or build from GitHub sources.
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